@article{
 title = {Molecular dynamics techniques for modeling G protein-coupled receptors},
 type = {article},
 year = {2016},
 identifiers = {[object Object]},
 pages = {69-75},
 volume = {30},
 websites = {http://dx.doi.org/10.1016/j.coph.2016.07.001},
 publisher = {Elsevier Ltd},
 id = {4f8372c0-639b-3cd6-84de-68cadfc81cc6},
 created = {2017-10-25T20:03:41.550Z},
 file_attached = {false},
 profile_id = {11c803fe-e925-36b5-adf2-c0ec2ac564b7},
 group_id = {964b17ba-8532-3020-9fad-40e29ba1344c},
 last_modified = {2017-10-25T20:03:41.550Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {McRobb2016},
 private_publication = {false},
 abstract = {G protein-coupled receptors (GPCRs) constitute a major class of drug targets and modulating their signaling can produce a wide range of pharmacological outcomes. With the growing number of high-resolution GPCR crystal structures, we have the unprecedented opportunity to leverage structure-based drug design techniques. Here, we discuss a number of advanced molecular dynamics (MD) techniques that have been applied to GPCRs, including long time scale simulations, enhanced sampling techniques, water network analyses, and free energy approaches to determine relative binding free energies. On the basis of the many success stories, including those highlighted here, we expect that MD techniques will be increasingly applied to aid in structure-based drug design and lead optimization for GPCRs.},
 bibtype = {article},
 author = {McRobb, Fiona M. and Negri, Ana and Beuming, Thijs and Sherman, Woody},
 journal = {Current Opinion in Pharmacology},
 number = {Md}
}

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